60 research outputs found
Evidence for Stable Square Ice from Quantum Monte Carlo
Recent experiments on ice formed by water under nanoconfinement provide
evidence for a two-dimensional (2D) `square ice' phase. However, the
interpretation of the experiments has been questioned and the stability of
square ice has become a matter of debate. Partially this is because the
simulation approaches employed so far (force fields and density functional
theory) struggle to accurately describe the very small energy differences
between the relevant phases. Here we report a study of 2D ice using an accurate
wave-function based electronic structure approach, namely Diffusion Monte Carlo
(DMC). We find that at relatively high pressure square ice is indeed the lowest
enthalpy phase examined, supporting the initial experimental claim. Moreover,
at lower pressures a `pentagonal ice' phase (not yet observed experimentally)
has the lowest enthalpy, and at ambient pressure the `pentagonal ice' phase is
degenerate with a `hexagonal ice' phase. Our DMC results also allow us to
evaluate the accuracy of various density functional theory exchange correlation
functionals and force field models, and in doing so we extend the understanding
of how such methodologies perform to challenging 2D structures presenting
dangling hydrogen bonds
Structure and stability of molecular crystals with many body dispersion inclusive density functional tight binding
Accurate prediction of structure and stability of molecular crystals is crucial in materials science and requires reliable modeling of long-range dispersion interactions. Semi-empirical electronic structure methods are computationally more efficient than their ab initio counterparts, allowing structure sampling with significant speedups. Here, we combine the Tkatchenko-Scheffler van-der-Waals method (TS) and the many body dispersion method (MBD) with third-order density functional tight-binding (DFTB3) via a charge population-based method. We find an overall good performance for the X23 benchmark database of molecular crystals, despite an underestimation of crystal volume that can be traced to the DFTB parametrization. We achieve accurate lattice energy predictions with DFT+MBD energetics on top of vdW-inclusive DFTB3 structures, resulting in a speedup of up to 3000 times compared to a full DFT treatment. This suggests that vdW-inclusive DFTB3 can serve as a viable structural prescreening tool in crystal structure prediction
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Liquid water contains the building blocks of diverse ice phases.
Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least 17 experimentally confirmed ice phases with enormous structural diversity. It remains a puzzle how or whether this multitude of arrangements in different phases of water are related. Here we investigate the structural similarities between liquid water and a comprehensive set of 54 ice phases in simulations, by directly comparing their local environments using general atomic descriptors, and also by demonstrating that a machine-learning potential trained on liquid water alone can predict the densities, lattice energies, and vibrational properties of the ices. The finding that the local environments characterising the different ice phases are found in water sheds light on the phase behavior of water, and rationalizes the transferability of water models between different phases
Free-energy landscape of polymer-crystal polymorphism
Polymorphism rationalizes how processing can control the final structure of a
material. The rugged free-energy landscape and exceedingly slow kinetics in the
solid state have so far hampered computational investigations. We report for
the first time the free-energy landscape of a polymorphic crystalline polymer,
syndiotactic polystyrene. Coarse-grained metadynamics simulations allow us to
efficiently sample the landscape at large. The free-energy difference between
the two main polymorphs, and , is further investigated by
quantum-chemical calculations. The two methods are in line with experimental
observations: they predict as the more stable polymorph at standard
conditions. Critically, the free-energy landscape suggests how the
polymorph may lead to experimentally observed kinetic traps. The combination of
multiscale modeling, enhanced sampling, and quantum-chemical calculations
offers an appealing strategy to uncover complex free-energy landscapes with
polymorphic behavior.Comment: 10 pages, 4 figure
Fast and accurate quantum Monte Carlo for molecular crystals
Computer simulation plays a central role in modern day materials science. The
utility of a given computational approach depends largely on the balance it
provides between accuracy and computational cost. Molecular crystals are a
class of materials of great technological importance which are challenging for
even the most sophisticated \emph{ab initio} electronic structure theories to
accurately describe. This is partly because they are held together by a balance
of weak intermolecular forces but also because the primitive cells of molecular
crystals are often substantially larger than those of atomic solids. Here, we
demonstrate that diffusion quantum Monte Carlo (DMC) delivers sub-chemical
accuracy for a diverse set of molecular crystals at a surprisingly moderate
computational cost. As such, we anticipate that DMC can play an important role
in understanding and predicting the properties of a large number of molecular
crystals, including those built from relatively large molecules which are far
beyond reach of other high accuracy methods
On the physisorption of water on graphene: Sub-chemical accuracy from many-body electronic structure methods
Molecular adsorption on surfaces plays a central role in catalysis,
corrosion, desalination, and many other processes of relevance to industry and
the natural world. Few adsorption systems are more ubiquitous or of more
widespread importance than those involving water and carbon, and for a
molecular level understanding of such interfaces water monomer adsorption on
graphene is a fundamental and representative system. This system is
particularly interesting as it calls for an accurate treatment of electron
correlation effects, as well as posing a practical challenge to experiments.
Here, we employ many-body electronic structure methodologies that can be
rigorously converged and thus provide faithful references for the
molecule-surface interaction. In particular, we use diffusion Monte-Carlo
(DMC), coupled cluster (CCSD(T)), as well as the random phase approximation
(RPA) to calculate the strength of the interaction between water and an
extended graphene surface. We establish excellent, sub-chemical, agreement
between the complementary high-level methodologies, and an adsorption energy
estimate in the most stable configuration of approximately -100\,meV is
obtained. We also find that the adsorption energy is rather insensitive to the
orientation of the water molecule on the surface, despite different binding
motifs involving qualitatively different interfacial charge reorganisation. In
producing the first demonstrably accurate adsorption energies for water on
graphene this work also resolves discrepancies amongst previously reported
values for this widely studied system. It also paves the way for more accurate
and reliable studies of liquid water at carbon interfaces with cheaper
computational methods, such as density functional theory and classical
potentials
Thermal Expansion of Carbamazepine:Systematic Crystallographic Measurements Challenge Quantum Chemical Calculations
We
report systematic temperature-dependent X-ray measurements on
the most stable carbamazepine polymorph. This active pharmaceutical
ingredient is used to demonstrate how the thermal expansion can probe
certain intermolecular interactions resulting in anisotropic expansion
behavior. We show that most structural features can be captured by
electronic structure calculations at the quasi-harmonic approximation
(QHA) provided a dispersion-corrected density functional based method
is employed. The impact of thermal expansion on the phonon modes and
hence free energy contributions is large enough to impact the relative
stability of different polymorphs
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